A Reinforcement Learning Inspired Latent Yield Based Adaptive Algorithm Switching Mechanism - 惯性聚合

推荐订阅源

Help Net Security

Future of Privacy Forum

The GitHub Blog

博客园 - 叶小钗

阮一峰的网络日志

Kaspersky official blog

Google Developers Blog

freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More

Privacy International News Feed

Cyber Attacks, Cyber Crime and Cyber Security

News | PayPal Newsroom

Schneier on Security

Microsoft Azure Blog

The Hacker News

Stack Overflow Blog

Security Latest

Microsoft Research Blog - Microsoft Research

Google Online Security Blog

博客园_首页

CXSECURITY Database RSS Feed - CXSecurity.com

Google DeepMind News

Y Combinator Blog

The Cloudflare Blog

Microsoft Security Blog

Cisco Talos Blog

钛媒体：引领未来商业与生活新知

Troy Hunt's Blog

Fox-IT International blog

Security @ Cisco Blogs

博客园 - 司徒正美

cs.CV updates on arXiv.org

Comments on: Blog

Threat Intelligence Blog | Flashpoint

LINUX DO - 最新话题

Tailwind CSS Blog

cs.LG updates on arXiv.org

Batch Normalization Amplifies Memorization and Privacy Risks Disentangled Double Machine Learning for Accurate Causal Effect Estimation Rethinking Federated Unlearning via the Lens of Memorization Streaming Reinforcement Learning under Partial Observability with Real-Time Recurrent Learning The Normalized Maximum Likelihood for Regular Non-Smooth Models: Measure-Theoretic Foundations and Geometric Sampling Evolving Robustness--Exploration Trade-off in Online Reinforcement Learning via Quantile Bayesian Risk MDPs ChainLearn: A Blockchain-Based Capacity-Aware Framework for Federated Ensemble Learning Assessing the Operational Viability of Foundation Models for Time Series Forecasting Generative Representation Learning on Hyper-relational Knowledge Graphs via Masked Discrete Diffusion Position: AI for Science Should Treat Measurement-to-Dataset Pipelines as Inference Components ChaosBench-Logic v2: Evaluating LLM Logical Reasoning over Dynamical Systems at Scale Private Adaptive Covariance Estimation via Gaussian Graphical Models LLM-AutoSciLab: Closed-Loop Scientific Discovery via Active Experimentation with LLMs SemanticZip: A Pilot Framework for Lossy Text Compression with LLMs as Semantic Decompressors A Large-Scale Dataset and Benchmark: Do Protein-Ligand Models Learn Binding Sites or Just Binding Likelihood? Hardware-Aware Federated Learning for Speech Emotion Recognition Momentum Streams for Optimizer-Inspired Transformers Not All Transitions Matter: Evidence from PPO A computational phase transition for learning-to-sample from Ising models Parameter Efficient Multi-Class Intelligent Scheduling for Multimodal Online Distributed Industrial Anomaly Detection Treatment Effect Estimation with Differentiated Networked Effect on Graph Data Towards Verifiable Transformers: Solver-Checkable Circuit Explanations Representation-Guided Discrete Molecular Graph Retrosynthesis Balancing Fairness, Privacy, and Accuracy: A Multitask Adversarial Framework for Centralized Data-Driven Systems A lift for input-convex neural network training Extracting Training Data from Diffusion Language Models via Infilling Agent-ToM: Learning to Monitor Autonomous LLM Agents via Theory-of-Mind Reasoning Signs Beat Floats: Low-Rank Double-Binary Adaptation for On-Device Fine-Tuning Faithfulness as Information Flow: Evaluating and Training Faithful Chain-of-Thought Reasoning Hermite-NGP: Gradient-Augmented Hash Encoding for Learning PDEs Cross-Domain Energy-Guided Diffusion Generation for Off-Dynamics Reinforcement Learning Active Learning for Stochastic Contextual Linear Bandits Truthful Online Preference Aggregation for LLM Fine-Tuning in Mobile Crowdsourcing Beyond Generative Priors: Minority Sampling with JEPA-Guided Diffusion CAFD: Concept-Aware DNN Fault Detection using VLMs Polymorphism Is Rotation: Operational Mechanistic Interpretability from a Two-Layer Transformer to Pythia-70m Discovering Lexical Gaps Using Embeddings from Multilingual LLMs WLNO: Wavelet-Laplace Neural Operator for Solving Partial Differential Equations Beyond Fixed Points: Superpolynomial Capacity of Asymmetric Hopfield Networks Feature Lottery? A Bifurcation Theory of Concept Emergence Feature Learning in Wide Neural Networks under $μ$P: Identifiability and Sparse-Dictionary Decomposition of the Mean-Field Limit A Unified Python Framework for Direct PPO-based Control of AHUs with Economizer Logic and CO2-Constrained Ventilation Optimizing Digital Therapeutic Interventions: Online Learning under Endogenous Adherence Knowledge Graph Modulated Deep Learning for Limited-Sample Clinical Data Analysis Beyond the Aggregation Dilemma: Prior-Retaining Decoupled Learning for Multimodal Graphs Complement Submodular Information Measures for Balanced and Robust Data Selection Cascade-KDE: Robust Time-Series Restoration under Out-of-Distribution Impulse Corruptions LLMs Show No Signs Of Individuated Metacognition The Perception-Physics Paradox: Probing Scientific Alignment with TC-Bench AI-Driven Adaptive Adversaries and the Erosion of Cryptographic Trust in Public Key Systems Rethinking Continual Anomaly Detection on the Edge: Benchmarking Under Realistic Industrial Conditions Synheart Capacity: A Theory-Driven Physiological Representation of Cognitive Capacity Dynamics from Wearable Signals Bilevel Optimization of Synthetic Trajectories for Multi-Turn LLM Fine-Tuning Omissive Bias in Religious Representation: Benchmarking LLM Answers to Everyday Ethical Decision-making Fourier Feature Pyramids for Physics-Informed Neural Networks Algometrics: Forecasting Under Algorithmic Feedback ChainzRule: Sample-Efficient, Robust Deep Learning Across Tabular, NLP, and Vision Tasks Learning Laplacian Eigenspace with Mass-Aware Neural Operators on Point Clouds From One-Pass SGD to Data Reuse: Mini-Batch Scaling Laws in Sketched Linear Regression Overcoming "Physics Shock" in Earth Observation A Heteroscedastic Uncertainty Framework for PINN-based Flood Inference Refined Analysis of Entropy-Regularized Actor-Critic LLMTabBench: Evaluating LLMs on Binary Tabular Classification From Zero to Few Shots Zeroth-Order Nonconvex Nonsmooth Optimization with Heavy-Tailed Noise PILOT: Policy-Informed Learned Optimization for Adaptive Deep Network Training LAPLEX: The FFT of Learnable Laplace Kernels Trajectory-Based Difficulty Scoring for Reliable Learning on Tabular Data RL with Learnable Textual Feedback: A Bilevel Approach ECHO: Terminal Agents Learn World Models for Free Temporal Concept Drift in Legal Judgment Prediction: Neural Baselines Across Three Epochs of Ukrainian Court Decisions On the Stability and Realizability of Recurrent Polynomial Surrogate Ternary Logic Gate Networks MindAlign: Bridging EEG, Vision, and Language for Zero-Shot Visual Decoding A Contractive Feedback Semantics for Reinforcement Learning Riemannian Archetypal Analysis: Interpretable non-linear data analysis on deformed star distributions Aligning Molecular Graph Explanations with Chemical Identity via InChIfied Invariants Verified SHAP: Provable Bounds for Exact Shapley Values of Neural Networks IterInject: Indirect Prompt Injection Against LLM Agents via Feedback-Guided Iterative Optimization Muon in Vision Transformers: Optimizer-Recipe Interactions and Gradient Spectra Mixture of Complementary Agents for Robust LLM Ensemble Lake Detection and Water Quality Estimation in Sentinel-2 Data PromptAudit: Auditing Prompt Sensitivity in LLM-Based Vulnerability Detection Federated Learning over Human-Body Communication for On-Body Edge Intelligence: A Survey, Taxonomy, and BODYFED-HBC Scheduling Vignette GEESE: Genotype-aware End-to-End Spatio-temporal Embedding for Behavioral Phenotyping PrivFusion: A Privacy-preserving Multi-Agent Framework for Harmonizing Distributed Datasets Generative OOD-regularized Model-based Policy Optimization Interdomain Attention: Beyond Token-Level Key-Value Memory Characterizing the Representational Capacity of Neural Processes TUBE: Tangent Upper Bound on Evidence for Discrete Diffusion Language Models Iterative Refinement Neural Operators are Learned Fixed-Point Solvers: A Principled Approach to Spectral Bias Mitigation CONF-KV: Confidence-Aware KV Cache Eviction with Mixed-Precision Storage for Long-Horizon LLM Spectral Probe-Circuits: A Three-Step Recipe for Identifying Attention-Head Circuits in Pretrained Transformers High-fidelity Modeling of Full-scale Pressurized Water Reactor Flow Fields for Machine Learning Applications Structure-Aware RAG: Structured Retrieval Augmented Generation from Noisy Data for Conversational Agents Hidden-State Privacy Has an Empty Middle CAffNet: Hard Constraint-Affine Neural Networks Reinforcement Learning for Reachability: Guaranteeing Asymptotic Optimality Deep ZakaiJ: Structured Filtering for Jump-Diffusion Time Series Forecasting An Effective-Rank Audit of Alignment-Induced Activation Shifts: Confound Control, Constructive Calibration, and Limits What Are We Actually Decoding? Source Attribution for Non-Invasive Brain-to-Language Retrieval CurveRL: Principled Distribution-Aware Context Reweighting for LLM Reasoning Filtered Posterior Mean Collections: A Unified Framework for Analytical Models of Diffusion Generalization

A Reinforcement Learning Inspired Latent Yield Based Adaptive Algorithm Switching Mechanism

Jayprakash S · 2026-05-26 · via cs.LG updates on arXiv.org

此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。原文来自 — 版权归原作者所有。